The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are ...The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.展开更多
Computer-aided diagnosis of pneumonia based on deep learning is a research hotspot.However,there are some problems that the features of different sizes and different directions are not sufficient when extracting the f...Computer-aided diagnosis of pneumonia based on deep learning is a research hotspot.However,there are some problems that the features of different sizes and different directions are not sufficient when extracting the features in lung X-ray images.A pneumonia classification model based on multi-scale directional feature enhancement MSD-Net is proposed in this paper.The main innovations are as follows:Firstly,the Multi-scale Residual Feature Extraction Module(MRFEM)is designed to effectively extract multi-scale features.The MRFEM uses dilated convolutions with different expansion rates to increase the receptive field and extract multi-scale features effectively.Secondly,the Multi-scale Directional Feature Perception Module(MDFPM)is designed,which uses a three-branch structure of different sizes convolution to transmit direction feature layer by layer,and focuses on the target region to enhance the feature information.Thirdly,the Axial Compression Former Module(ACFM)is designed to perform global calculations to enhance the perception ability of global features in different directions.To verify the effectiveness of the MSD-Net,comparative experiments and ablation experiments are carried out.In the COVID-19 RADIOGRAPHY DATABASE,the Accuracy,Recall,Precision,F1 Score,and Specificity of MSD-Net are 97.76%,95.57%,95.52%,95.52%,and 98.51%,respectively.In the chest X-ray dataset,the Accuracy,Recall,Precision,F1 Score and Specificity of MSD-Net are 97.78%,95.22%,96.49%,95.58%,and 98.11%,respectively.This model improves the accuracy of lung image recognition effectively and provides an important clinical reference to pneumonia Computer-Aided Diagnosis.展开更多
Sensors play an important role in shaping and monitoring human health.Exploration of methods to use Fiber Bragg Grating(FBG)with enhanced sensitivity has attracted great interest in the field of medical research.In th...Sensors play an important role in shaping and monitoring human health.Exploration of methods to use Fiber Bragg Grating(FBG)with enhanced sensitivity has attracted great interest in the field of medical research.In this paper,a novel apodization function is proposed and performance evaluation and optimization of the same have been made.A comparison was conducted between various existing apodization functions and the proposed one based on optical characteristics and sensor parameters.The results evince the implementation of the proposed apodization function for vital sign measurement.The optical characteristics considered for evaluation are Peak Resonance Reflectivity level,Side Lobes Reflectivity level and FullWidth HalfMaximum(FWHM).The proposed novel apodization novel function has better FWHM,which is narrower than the FWHM of uniform FBG.Sensor characteristics like a quality parameter,detection accuracy and sensitivity also show improvement.The proposed novel apodization function is demonstrated to have a better shift in wavelength in terms of temperature and pulse measurement than the existing functions.The sensitivity of the proposed apodized function is enhanced with a Poly-dimethylsiloxane coating of varying thickness,which is 6 times and 5.14 times greater than uniform Fiber Bragg grating and FBG with the proposed novel apodization function,respectively,enhancing its utilization in the field of medicine.展开更多
The piezoelectric film electro-deposition for optical fiber sensor with ZnO coating is studied. The zinc oxide plating film is made on the copper surface directly by cathodic electro-deposition in the Zn（NO3）2 singl...The piezoelectric film electro-deposition for optical fiber sensor with ZnO coating is studied. The zinc oxide plating film is made on the copper surface directly by cathodic electro-deposition in the Zn（NO3）2 single salt aqueous solution systems. The influences of main experimental conditions on the properties of ZnO thin film in the electro-deposition processes are analyzed and a stable, practical and economic technique is obtained.展开更多
Workflow management is concerned with automated support for business processes.Workflow management systems are driven by process models specifying the tasks that need to be executed,the order in which they can be exec...Workflow management is concerned with automated support for business processes.Workflow management systems are driven by process models specifying the tasks that need to be executed,the order in which they can be executed,which resources are authorised to perform which tasks,and data that is required for,and produced by,these tasks.As workflow instances may run over a sustained period of time,it is important that workflow specifications be checked before they are deployed.Workflow verification is usually concerned with control-flow dependencies only;however,transition conditions based on data may further restrict possible choices between tasks.In this paper we extend workflow nets where transitions have concrete conditions associated with them,called WTC-nets.We then demonstrate that we can determine which execution paths of a WTC-net that are possible according to the control-flow dependencies,are actually possible when considering the conditions based on data.Thus,we are able to more accurately determine at design time whether a workflow net with transition conditions is sound.展开更多
For the course of“Data Structures”,this paper introduces the importance and existing problems of the data structure course.Through the literature and the current teaching in major universities,the existing teaching ...For the course of“Data Structures”,this paper introduces the importance and existing problems of the data structure course.Through the literature and the current teaching in major universities,the existing teaching methods and their disadvantages are analyzed.The authors put forward teaching reform suggestions and designed an online course platform.展开更多
Objective: Medical data mining and sharing is an important process in E-Health applications. However, because these data consist of a large amount of personal private information of patients, there is the risk of priv...Objective: Medical data mining and sharing is an important process in E-Health applications. However, because these data consist of a large amount of personal private information of patients, there is the risk of privacy disclosure when sharing and mining. Therefore, ensuring the security of medical big data in the process of publishing, sharing, and mining has become the focus of current research. The objective of our study is to design a framework based on a differential privacy protection mechanism to ensure the secure sharing of medical data. We developed a privacy protection query language (PQL) that integrates multiple data mining methods and provides a secure sharing function.Methods: This study is mainly performed in Xuzhou Medical University, China and designs three sub-modules: a parsing module, mining module, and noising module. Each module encapsulates different computing methods, such as a composite parser and a noise theory. In the PQL framework, we apply the differential privacy theory to the results of the computing between modules to guarantee the security of various mining algorithms. These computing devices operate independently, but the mining results depend on their cooperation. In addition, PQL is encapsulated in MNSSp3 that is a data mining and security sharing platform and the data comes from public data sets, such as UCBI. The public data set (NCBI database) was used as the experimental data, and the data collection time was January 2020.Results: We designed and developed a query language that provides functions for medical data mining, sharing, and privacy preservation. We theoretically proved the performance of the PQL framework. The experimental results show that the PQL framework can ensure the security of each mining result and the availability of the output results is above 97%.Conclusion: Our framework enables medical data providers to securely share health data or treatment data and develops a usable query language, based on a differential privacy mechanism, that enables researche展开更多
Talent cultivation is the primary task of universities.Local general undergraduate colleges and universities should adhere to the basic guidelines of systematization,practicality and integration,continuously explore t...Talent cultivation is the primary task of universities.Local general undergraduate colleges and universities should adhere to the basic guidelines of systematization,practicality and integration,continuously explore the concept of"studentcentered"talent cultivation,and build a threedimensional practical teaching system from three aspects:strengthening the planning and design of the three-dimensional practical teaching system;building an internal and external practical teaching platform;and improving the evaluation and guarantee system of practical teaching quality.The system of practical teaching quality evaluation and guarantee is improved.In order to improve the cultivation ability of applied talents in all aspects.展开更多
基金funded by National Natural Science Foundation of China No.62062003Ningxia Natural Science Foundation Project No.2023AAC03293.
文摘The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.
基金supported in part by the National Natural Science Foundation of China(Grant No.62062003)Natural Science Foundation of Ningxia(Grant No.2023AAC03293).
文摘Computer-aided diagnosis of pneumonia based on deep learning is a research hotspot.However,there are some problems that the features of different sizes and different directions are not sufficient when extracting the features in lung X-ray images.A pneumonia classification model based on multi-scale directional feature enhancement MSD-Net is proposed in this paper.The main innovations are as follows:Firstly,the Multi-scale Residual Feature Extraction Module(MRFEM)is designed to effectively extract multi-scale features.The MRFEM uses dilated convolutions with different expansion rates to increase the receptive field and extract multi-scale features effectively.Secondly,the Multi-scale Directional Feature Perception Module(MDFPM)is designed,which uses a three-branch structure of different sizes convolution to transmit direction feature layer by layer,and focuses on the target region to enhance the feature information.Thirdly,the Axial Compression Former Module(ACFM)is designed to perform global calculations to enhance the perception ability of global features in different directions.To verify the effectiveness of the MSD-Net,comparative experiments and ablation experiments are carried out.In the COVID-19 RADIOGRAPHY DATABASE,the Accuracy,Recall,Precision,F1 Score,and Specificity of MSD-Net are 97.76%,95.57%,95.52%,95.52%,and 98.51%,respectively.In the chest X-ray dataset,the Accuracy,Recall,Precision,F1 Score and Specificity of MSD-Net are 97.78%,95.22%,96.49%,95.58%,and 98.11%,respectively.This model improves the accuracy of lung image recognition effectively and provides an important clinical reference to pneumonia Computer-Aided Diagnosis.
基金supported in part by Universiti Malaya,and ACU UK under Project No.IF063-2021.
文摘Sensors play an important role in shaping and monitoring human health.Exploration of methods to use Fiber Bragg Grating(FBG)with enhanced sensitivity has attracted great interest in the field of medical research.In this paper,a novel apodization function is proposed and performance evaluation and optimization of the same have been made.A comparison was conducted between various existing apodization functions and the proposed one based on optical characteristics and sensor parameters.The results evince the implementation of the proposed apodization function for vital sign measurement.The optical characteristics considered for evaluation are Peak Resonance Reflectivity level,Side Lobes Reflectivity level and FullWidth HalfMaximum(FWHM).The proposed novel apodization novel function has better FWHM,which is narrower than the FWHM of uniform FBG.Sensor characteristics like a quality parameter,detection accuracy and sensitivity also show improvement.The proposed novel apodization function is demonstrated to have a better shift in wavelength in terms of temperature and pulse measurement than the existing functions.The sensitivity of the proposed apodized function is enhanced with a Poly-dimethylsiloxane coating of varying thickness,which is 6 times and 5.14 times greater than uniform Fiber Bragg grating and FBG with the proposed novel apodization function,respectively,enhancing its utilization in the field of medicine.
基金Jiangxi Natural Science Foundation(No.2007GZW1582)the Key Laboratory of New Processing Technology for Nonferros and Materials,Guangxi Zhuang Autonomous Region
文摘The piezoelectric film electro-deposition for optical fiber sensor with ZnO coating is studied. The zinc oxide plating film is made on the copper surface directly by cathodic electro-deposition in the Zn（NO3）2 single salt aqueous solution systems. The influences of main experimental conditions on the properties of ZnO thin film in the electro-deposition processes are analyzed and a stable, practical and economic technique is obtained.
基金Project supported by the National Science and Technology Major Project of China (No.2010ZX01042-002-002-01)the National Basic Research Program (973) of China (No.2009CB320700)the National Natural Science Foundation of China (Nos.61073005 and 61003099)
文摘Workflow management is concerned with automated support for business processes.Workflow management systems are driven by process models specifying the tasks that need to be executed,the order in which they can be executed,which resources are authorised to perform which tasks,and data that is required for,and produced by,these tasks.As workflow instances may run over a sustained period of time,it is important that workflow specifications be checked before they are deployed.Workflow verification is usually concerned with control-flow dependencies only;however,transition conditions based on data may further restrict possible choices between tasks.In this paper we extend workflow nets where transitions have concrete conditions associated with them,called WTC-nets.We then demonstrate that we can determine which execution paths of a WTC-net that are possible according to the control-flow dependencies,are actually possible when considering the conditions based on data.Thus,we are able to more accurately determine at design time whether a workflow net with transition conditions is sound.
基金supported in part by grants from Qinglan Project of Jiangsu Province(2020)High-level demonstration construction project of Sino-foreign cooperation in running schools in Jiangsu Province,Jiangsu Higher Educational Technology Research Association-2019 Higher Education Informatization Research Project(2019JSETKT035)Ideological and Political Special Project of Philosophy and Social Science Research Projects in Colleges and Universities in 2019(2019SJB422).
文摘For the course of“Data Structures”,this paper introduces the importance and existing problems of the data structure course.Through the literature and the current teaching in major universities,the existing teaching methods and their disadvantages are analyzed.The authors put forward teaching reform suggestions and designed an online course platform.
基金This work was supported by the Special Investigation on Science and Technology Basic Resources of the MOST of China(No.2019FY100103)the National Natural Science Founda-tion of China(No.62003291)+1 种基金the Xuzhou Science and Technology Project(No.KC20112)the Industry Univer-sity-Research-Cooperation Project in Jiangsu Province(No.BY2018124).
文摘Objective: Medical data mining and sharing is an important process in E-Health applications. However, because these data consist of a large amount of personal private information of patients, there is the risk of privacy disclosure when sharing and mining. Therefore, ensuring the security of medical big data in the process of publishing, sharing, and mining has become the focus of current research. The objective of our study is to design a framework based on a differential privacy protection mechanism to ensure the secure sharing of medical data. We developed a privacy protection query language (PQL) that integrates multiple data mining methods and provides a secure sharing function.Methods: This study is mainly performed in Xuzhou Medical University, China and designs three sub-modules: a parsing module, mining module, and noising module. Each module encapsulates different computing methods, such as a composite parser and a noise theory. In the PQL framework, we apply the differential privacy theory to the results of the computing between modules to guarantee the security of various mining algorithms. These computing devices operate independently, but the mining results depend on their cooperation. In addition, PQL is encapsulated in MNSSp3 that is a data mining and security sharing platform and the data comes from public data sets, such as UCBI. The public data set (NCBI database) was used as the experimental data, and the data collection time was January 2020.Results: We designed and developed a query language that provides functions for medical data mining, sharing, and privacy preservation. We theoretically proved the performance of the PQL framework. The experimental results show that the PQL framework can ensure the security of each mining result and the availability of the output results is above 97%.Conclusion: Our framework enables medical data providers to securely share health data or treatment data and develops a usable query language, based on a differential privacy mechanism, that enables researche
文摘Talent cultivation is the primary task of universities.Local general undergraduate colleges and universities should adhere to the basic guidelines of systematization,practicality and integration,continuously explore the concept of"studentcentered"talent cultivation,and build a threedimensional practical teaching system from three aspects:strengthening the planning and design of the three-dimensional practical teaching system;building an internal and external practical teaching platform;and improving the evaluation and guarantee system of practical teaching quality.The system of practical teaching quality evaluation and guarantee is improved.In order to improve the cultivation ability of applied talents in all aspects.
